Mass spectrometric imaging is an emerging tool in post genomic sciences such as proteomics, lipidomics and metabolomics.
Lipidomics, after genomics and proteomics, is a rapidly expanding research field that studies cellular lipidomes and the organisational hierarchy of lipid and protein constituents mediating life processes. Lipidomics is greatly facilitated by recent advances in, and novel applications of, electrospray ionization mass spectrometry (ESI/MS).
Moreover, Matrix Assisted Laser Desorption Ionization (MALDI) imaging mass spectrometry enables biomolecules to be analyzed directly from tissue sections, providing information on spatial distribution of analytes within the tissue sample. This involves the analysis of the differences in the chemical makeup of different areas of the substrate. Irradiation of areas of the substrate of interest by laser light in the presence of a matrix material produces ions that can be analysed by mass spectrometry, typically Time of Flight mass spectrometry (ToF).
Limitation of MALDI imaging is the complexity of the data collected, especially in the case of a non-targeted, open platform experiment.
To overcome this limitation, MALDI imaging data is typically arranged into different sections, a way of reducing the data complexity. In this case the ions from areas of the substrate that are in close relationship are added together to produce overall spectra for these sections within the substrate. However, using this procedure means that data can be lost and that differences between the chemical make up of areas within each section of the substrate may not be identified.
It is therefore desirable to find a method of analysis which will use all the data and differentiate between all the different areas of the substrate in an efficient way to identify information of interest relating to the sample.